Instructions to use research-dump/bert_base_year_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/bert_base_year_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/bert_base_year_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/bert_base_year_classifier") model = AutoModelForSequenceClassification.from_pretrained("research-dump/bert_base_year_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f32c97f9cf7ac6ceb5970397fd09eb056a2b58b5f31c5a7e75a5a6361c9be20e
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size 438002804
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